My personal data, and likely yours, is in more hands than ever. Tech
firms, data brokers and political consultants build profiles of what they
know — or think they can reasonably guess — about your purchasing habits,
personality, hobbies and even what political issues you care about.

You can find out what those companies know about you but be prepared to be
stubborn. Very stubborn. To demonstrate how this works, we’ve chosen a
couple of representative companies from three major categories: data
brokers, big tech firms and political data consultants.

Two years ago, I moderated a panel at SXSW called “Is Your
Biological Data Safe?” Looking at the panelists—a woman who runs a DIY
bio lab, 23andMe’s privacy officer, and an FBI agent—it was not hard to
determine at the time that the answer was, and is, “no.”

The investigators collected a decade’s worth of winners from lotteries
around the country associated with the Multi-State Lottery Association. They
loaded data from approximately 45,000 winning tickets into Microsoft Excel
spreadsheets and searched for any connections to Eddie Tipton. They reviewed
Tipton’s Facebook friends, pulled phone records and looked for matches with
the spreadsheet.

For a lot of people, their social network is already out in the open.
Provided by themselves.

The National Security Agency vacuumed up more than 534 million records of
phone calls and text messages from American telecommunications providers
like AT&T and Verizon last year — more than three times what it
collected in 2016, a new
report revealed on Friday.

Tech

In a dank corner of the internet, it is possible to find actresses from
Game of Thrones or Harry Potter engaged in all manner of sex acts. Or at
least to the world the carnal figures look like those actresses, and the
faces in the videos are indeed their own. Everything south of the neck,
however, belongs to different women. An artificial intelligence has almost
seamlessly stitched the familiar visages into pornographic scenes, one face
swapped for another. The genre is one of the cruelest, most invasive forms
of identity theft invented in the internet era. At the core of the cruelty
is the acuity of the technology: A casual observer can’t easily detect the
hoax.

This development, which has been the subject of much hand-wringing in the
tech press, is the work of a programmer who goes by the nom de hack
“deepfakes.” And it is merely a beta version of a much more ambitious
project. One of deepfakes’s compatriots told Vice’s Motherboard site in
January that he intends to democratize this work. He wants to refine the
process, further automating it, which would allow anyone to transpose the
disembodied head of a crush or an ex or a co-worker into an extant
pornographic clip with just a few simple steps. No technical knowledge would
be required. And because academic and commercial labs are developing even
more-sophisticated tools for non-pornographic purposes—algorithms that map
facial expressions and mimic voices with precision—the sordid fakes will
soon acquire even greater verisimilitude.

From health care to transportation to national security, AI has the
potential to improve lives. But it comes with fears about economic
disruption and a brewing “AI arms race .” Like any transformational change,
it’s complicated. Perhaps the biggest AI myth is that we can be confident
about its future effects. Here are five others.

The gambling industry is increasingly using artificial intelligence to
predict consumer habits and personalise promotions to keep gamblers hooked,
industry insiders have revealed.

Current and former gambling industry employees have described how people’s
betting habits are scrutinised and modelled to manipulate their future
behaviour.

“The industry is using AI to profile customers and predict their behaviour
in frightening new ways,” said Asif, a digital marketer who previously
worked for a gambling company. “Every click is scrutinised in order to
optimise profit, not to enhance a user’s experience.”

Note that the last quoted phrase applies to basically any service that
converts clicks / engagement / attention into money.

That’s what tests are for, and engineers learn from their mistakes and
oversights. Liberal capitalist democracy, however, isn’t great with
do-overs. In the political realm, there’s a fear that any flexible or
dynamic process would be subject to tyrannical abuse, and it’s better to
just wait until the next election. When it comes to property, possession is
nine-tenths of the law; good luck trying to get your money back due to
unfairness. And then there’s our system’s ultimate exploit: regulatory
capture. That’s like if the twitchy robot used its ill-gotten energy to take
over the computer and make sure the error never got patched. What looked
like a glitch becomes the system’s defining characteristic, which might help
explain why we all walk around now by slamming our face against the floor.

A team of researchers from the National Research Nuclear University MEPhI,
the National Research Center Kurchatov Institute and the Voronezh State
University has developed a new learning algorithm that allows a neural
network to identify a writer's gender by the written text on a computer with
up to 80 percent accuracy.